class_docstr: ARLSTem stemmer : a light Arabic Stemming algorithm without any dictionary.
  Department of Telecommunication & Information Processing. USTHB University,
  Algiers, Algeria.
  ARLSTem.stem(token) returns the Arabic stem for the input token.
  The ARLSTem Stemmer requires that all tokens are encoded using Unicode
  encoding.
class_docstr_tok: ["ARLSTem","stemmer",":","a","light","Arabic","Stemming","algorithm","without","any","dictionary",".","Department","of","Telecommunication","&","Information","Processing",".","USTHB","University",",","Algiers",",","Algeria",".","ARLSTem.stem","(","token",")","returns","the","Arabic","stem","for","the","input","token",".","The","ARLSTem","Stemmer","requires","that","all","tokens","are","encoded","using","Unicode","encoding","."]
docstr: call this function to get the word's stem based on ARLSTem .
docstr_tok: ["call","this","function","to","get","the","word","'s","stem","based","on","ARLSTem","."]
code: def stem(self, token):
      """
      call this function to get the word's stem based on ARLSTem .
      """
      try:
          if token is None:
              raise ValueError(
                  "The word could not be stemmed, because \
                                   it is empty !"
              )
          # remove Arabic diacritics and replace some letters with others
          token = self.norm(token)
          # strip common prefixes of the nouns
          pre = self.pref(token)
          if pre is not None:
              token = pre
          # strip the suffixes which are common to nouns and verbs
          token = self.suff(token)
          # transform a plural noun to a singular noun
          ps = self.plur2sing(token)
          if ps is None:
              # transform from the feminine form to the masculine form
              fm = self.fem2masc(token)
              if fm is not None:
                  return fm
              else:
                  if pre is None:  # if the prefixes are not stripped
                      # strip the verb prefixes and suffixes
                      return self.verb(token)
          else:
              return ps
          return token
      except ValueError as e:
          print(e)
  
file_path: nltk/nltk/stem/arlstem.py
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 2 for calling the ARLSTem obj's underlying member method code with example usage: obj.stem(token) and returns: token, ps, fm, self